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New Bengali cyberbullying corpus incorporates conversational context

By PulseAugur Editorial · [1 sources] ·

Researchers have developed BenCoDiC, a new corpus designed to address the limitations of existing Bengali cyberbullying datasets. This large-scale resource comprises over 50,000 instances collected from Bengali political news discourse on YouTube, preserving conversational context like replies and user interactions. The corpus features a nine-dimensional schema for detailed analysis and was annotated through a rigorous two-tier human process, achieving high inter-annotator agreement. Initial experiments using transformer models indicate that incorporating conversational context improves cyberbullying detection accuracy. AI

IMPACT This corpus could enable more nuanced AI-driven detection of cyberbullying in Bengali political discourse.

RANK_REASON The cluster describes a new academic paper detailing the creation of a specialized dataset for NLP research. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New Bengali cyberbullying corpus incorporates conversational context

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The cluster describes a new academic paper detailing the creation of a specialized dataset for NLP research. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Md. Nesarul Hoque, Rudra Pratap Deb Nath, Umme Salma, Shima Chakraborty, Md. Hanif Seddiqui ·

    BenCoDiC: A Large-Scale Contextual Cyberbullying Corpus for Bengali Political News Discourse FULL VERSION

    arXiv:2610.13121v1 Announce Type: new Abstract: Cyberbullying is a growing concern in online communities, yet existing Bengali corpora remain limited in contextual information, annotation transparency, scale, accessibility, and support for multidimensional analysis, thereby hinde…

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